Sensing and control in bandwidth-limited systems: A Kalman filter approach

Cooperative systems, like those found in networks of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), are typically distributed over large geographical areas. This geographic dispersion forces reliance on wireless communications to implement the control systems for these networks. As the number of nodes within the system grows, the bandwidth required to continuously update all nodes exceeds available bandwidth. This forces the system engineers to implement a prioritization scheme to determine which nodes will be updated during each frame. In this paper, we consider the design of protocols to prioritize the communications of sensing and control data. We consider a control system that uses a Kalman filter to supply optimal estimates of the positions for a group of maneuvering targets in the presence of measurement noise and lost data. The filter innovations provide estimates of the magnitude of statistical deviations from the state estimates, as well as deviations from planned profiles. Thus, we propose protocols that use the filter innovations to prioritize the sensing and control traffic. We compare the performance of this approach to a round-robin protocol and to the performance of a Kalman filter with no bandwidth constraints. We show that using the filter innovations offers a significant performance improvement over the round-robin protocol.